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Among the most damaging characteristics of the covid-19 pandemic has been itsdisproportionate effect on disadvantaged communities. As the outbreak hasspread globally, factors such as systemic racism, marginalisation, andstructural inequality have created path dependencies that have led to poorhealth outcomes. These social determinants of infectious disease andvulnerability to disaster have converged to affect already disadvantagedcommunities with higher levels of economic instability, disease exposure,infection severity, and death. Artificial intelligence (AI) technologies are animportant part of the health informatics toolkit used to fight contagiousdisease. AI is well known, however, to be susceptible to algorithmic biasesthat can entrench and augment existing inequality. Uncritically deploying AI inthe fight against covid-19 thus risks amplifying the pandemic's adverse effectson vulnerable groups, exacerbating health inequity. In this paper, we claimthat AI systems can introduce or reflect bias and discrimination in three ways:in patterns of health discrimination that become entrenched in datasets, indata representativeness, and in human choices made during the design,development, and deployment of these systems. We highlight how the use of AItechnologies threaten to exacerbate the disparate effect of covid-19 onmarginalised, under-represented, and vulnerable groups, particularly black,Asian, and other minoritised ethnic people, older populations, and those oflower socioeconomic status. We conclude that, to mitigate the compoundingeffects of AI on inequalities associated with covid-19, decision makers,technology developers, and health officials must account for the potentialbiases and inequities at all stages of the AI process.

Does "AI" stand for augmenting inequality in the era of covid-19 healthcare?